90 



Fishery Bulletin 102(1) 



E 



E 



Prytherch 1999 



Radio 1999 



95 105 115 125 135 145 155 165 



B 



D 



Haystacks 1999 



95 115 135 155 175 195 



95 115 135 155 175 195 



Julian day 



Julian day 



Figure 11 



Temporal density patterns from (A) Duke Beach, 1999; (B) Haystacks Marsh, 1999; (C) Prytherch Marsh, 

 1999; (D) Towne Beach, 1999; (E) Radio Beach, 1999; (F) Duke Beach, 1998; and (G) Prytherch Marsh 1998. 

 Densities are corrected for gear bias (see Kellison, 2000). 



Model utility and implications 



Although model results varied considerably under the 

 various density-mortality relationships, the overall pre- 

 dictions that survival would be maximized and economic 

 costs minimized when relatively large fish were released 

 early in the season were unaffected by the density- 

 mortality relationship. These results suggest that manag- 

 ers may use this model to make inferences about optimal 

 release scenarios even if density-mortality relationships 

 are unknown. Additionally, these results have important 

 implications for the cost efficiency of stock enhancement 

 programs. Managers can use the model to determine 



the release scenarios under which they can 1) maxi- 

 mize the number of survivors, given a financial limit 

 (e.g. given a budget of x dollars, what release scenario 

 or scenarios will produce the greatest number of survi- 

 vors?), and 2) minimize costs, given a goal of number-of- 

 survivors-produced (e.g. given a goal of producing 

 .v survivors, what release scenario or scenarios will be most 

 cost efficient?). 



In conclusion, the compartmental model used in this 

 study provides an example of a relatively easy-to-develop 

 predictive tool with which to make inferences about the 

 ecological and economic potential of stock enhancement, in 

 relation to alternative management approaches, to rebuild 

 depleted fisheries. 



